Contextualizing AI Education for K-12 Students to Enhance Their Learning of AI Literacy Through Culturally Responsive Approaches

被引:0
|
作者
Amy Eguchi
Hiroyuki Okada
Yumiko Muto
机构
[1] University of California San Diego,Department of Education Studies
[2] Tamagawa University,Brain Science Institute, Graduate School of Engineering, Graduate School of Brain Sciences
[3] Tamagawa University,Brain Research institute
来源
关键词
Contextualization; AI literacy; Culturally responsive pedagogy; K-12 AI education; Cultural context;
D O I
暂无
中图分类号
学科分类号
摘要
AI has become ubiquitous in our society, accelerated by the speed of the development of machine learning algorithms and voice and facial recognition technologies used in our everyday lives. Furthermore, AI-enhanced technologies and tools are no strangers in the field of education. It is more evident that it is important to prepare K-12 population of students for their future professions as well as citizens capable of understanding and utilizing AI-enhanced technologies in the future. In response to such needs, the authors started a collaborative project aiming to provide a K-12 AI curriculum for Japanese students. However, the authors soon realized that it is important to contextualize the learning experience for the targeted K-12 students. The paper aims at introducing the idea of contextualizing AI education and learning experience of K-12 students with examples and tips using the work-in-progress version of the contextualized curriculum using culturally responsive approaches to promote the awareness and understanding of AI ethics among middle school students.
引用
收藏
页码:153 / 161
页数:8
相关论文
共 50 条
  • [1] Contextualizing AI Education for K-12 Students to Enhance Their Learning of AI Literacy Through Culturally Responsive Approaches
    Eguchi, Amy
    Okada, Hiroyuki
    Muto, Yumiko
    [J]. KI - Kunstliche Intelligenz, 2021, 35 (02): : 153 - 161
  • [2] Contextualizing AI Education for K-12 Students to Enhance Their Learning of AI Literacy Through Culturally Responsive Approaches
    Eguchi, Amy
    Okada, Hiroyuki
    Muto, Yumiko
    [J]. KUNSTLICHE INTELLIGENZ, 2021, 35 (02): : 153 - 161
  • [3] K-12 Education in the Age of AI: A Call to Action for K-12 AI Literacy
    Ning Wang
    James Lester
    [J]. International Journal of Artificial Intelligence in Education, 2023, 33 : 228 - 232
  • [4] K-12 Education in the Age of AI: A Call to Action for K-12 AI Literacy
    Wang, Ning
    Lester, James
    [J]. INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION, 2023, 33 (02) : 228 - 232
  • [5] From Primary Education to Premium Workforce: Drawing on K-12 Approaches for Developing AI Literacy
    Kaspersen, Magnus Hoholt
    Musaeus, Line Have
    Bilstrup, Karl-Emil Kjaer
    Petersen, Marianne Graves
    Iversen, Ole Sejer
    Dindler, Christian
    Dalsgaard, Peter
    [J]. PROCEEDINGS OF THE 2024 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYTEMS (CHI 2024), 2024,
  • [6] A Year in K-12 AI Education
    Touretzky, David
    Gardner-McCune, Christina
    Breazeal, Cynthia
    Martin, Fred
    Seehorn, Deborah
    [J]. AI MAGAZINE, 2019, 40 (04) : 88 - 90
  • [7] AI K-12 Education Service
    Kandlhofer, Martin
    Steinbauer, Gerald
    [J]. KUNSTLICHE INTELLIGENZ, 2021, 35 (02): : 125 - 126
  • [8] AI literacy in K-12: a systematic literature review
    Casal-Otero, Lorena
    Catala, Alejandro
    Fernandez-Morante, Carmen
    Taboada, Maria
    Cebreiro, Beatriz
    Barro, Senen
    [J]. INTERNATIONAL JOURNAL OF STEM EDUCATION, 2023, 10 (01)
  • [9] AI literacy in K-12: a systematic literature review
    Lorena Casal-Otero
    Alejandro Catala
    Carmen Fernández-Morante
    Maria Taboada
    Beatriz Cebreiro
    Senén Barro
    [J]. International Journal of STEM Education, 10
  • [10] Exploring Approaches for Teaching Cybersecurity and AI for K-12
    Cai, Yu
    Youngstrom, Drew
    Zhang, Wenbin
    [J]. 2023 23RD IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS, ICDMW 2023, 2023, : 1559 - 1564